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Record W227867369 · doi:10.13182/nt06-a3695

A Physics Study on Thorium Fuel Recycling in a CANDU Reactor Using Dry Process Technology

2006· article· en· W227867369 on OpenAlexaboutno aff
Hangbok Choi, Chang Je Park

Bibliographic record

VenueNuclear Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsnot available
Fundersnot available
KeywordsSpent nuclear fuelThorium fuel cycleFuel cycleNuclear engineeringUraniumNuclear fuelEnvironmental scienceThoriumEnriched uraniumNuclear fuel cycleLiquid fluoride thorium reactorNatural uraniumDepleted uraniumWaste managementNuclear reactorNuclear physicsEngineeringPhysics

Abstract

fetched live from OpenAlex

Dry process fuel technology has high proliferation resistance, which is one of the important goals of the Generation-IV nuclear energy system developments. It is expected that dry process fuel technology can be applied not only to existing but also to future nuclear systems. In this study, the homogeneous ThO2-UO2 fuel cycle and the heterogeneous ThO2-DUPIC fuel cycle options of a Canada deuterium uranium (CANDU) reactor were assessed, which included a neutronic feasibility analysis of recycling spent fuels. Parametric calculations were also performed for reactivity coefficients and isotopic content changes for various initial fuel conditions. The results of the physics calculations have shown that it is feasible to recycle the thorium fuel through the dry process option in the CANDU reactor, which in turn significantly improves natural uranium savings and diminishes spent fuel. However, further investigation of the dry process option, which is technically and economically feasible for thorium-abundant dioxide fuel, is required.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.010
GPT teacher head0.229
Teacher spread0.218 · 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

Citations6
Published2006
Admission routes1
Has abstractyes

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