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Record W2147226990 · doi:10.1109/tns.2004.842722

Regional overpower protection system analysis for the direct use of spent pressurized water reactor fuel in CANDU Reactors (DUPIC)

2005· article· en· W2147226990 on OpenAlexaboutno aff
Chang Joon Jeong, Hangbok Choi

Bibliographic record

VenueIEEE Transactions on Nuclear Science · 2005
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsnot available
Fundersnot available
KeywordsNuclear engineeringNatural uraniumNatural circulationEnvironmental scienceThorium fuel cyclePressurized water reactorUraniumMOX fuelPhysicsNuclear physicsEngineering

Abstract

fetched live from OpenAlex

The regional overpower protection (ROP) system of a Canada deuterium uranium (CANDU) reactor was assessed for the direct use of spent pressurized water reactor fuel in CANDU reactors (DUPIC), including the validation of the Winfrith improved multigroup scheme (WIMS)/reactor fuelling simulation program (RFSP)/reduction power (ROVER) code system used for the calculation of the ROP trip setpoint (TSP). Comparative calculations showed that the WIMS/RFSP/ROVER code system produced results consistent with the current design code system for estimating the ROP TSP of the standard natural uranium CANDU reactor. For the DUPIC fuel CANDU core, the ROP TSP was estimated to be 123.4%, which was almost the same as that of the standard natural uranium core. The extra margin of the ROP TSP for the DUPIC fuel system was enhanced by the flattened axial channel power distribution as well as the reduced refueling ripple of the channel power. This study has shown that the DUPIC fuel does not deteriorate the current ROP TSP designed for the natural uranium CANDU reactor.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.206
Teacher spread0.180 · 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

Citations2
Published2005
Admission routes1
Has abstractyes

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