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Record W4232772732 · doi:10.13182/nt01-a3190

Economic Analysis on Direct Use of Spent Pressurized Water Reactor Fuel in CANDU Reactors—I: DUPIC Fuel Fabrication Cost

2001· article· en· W4232772732 on OpenAlexaboutno aff
Hangbok Choi, Won Il Ko, Myung Seung Yang

Bibliographic record

VenueNuclear Technology · 2001
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsnot available
FundersOak Ridge National LaboratoryInternational Atomic Energy AgencyKorea Atomic Energy Research Institute
KeywordsPressurized water reactorEnvironmental scienceCapital costNuclear engineeringDecay heatWaste managementSpent nuclear fuelEngineering

Abstract

fetched live from OpenAlex

A preliminary conceptual design of a Direct Use of spent Pressurized water reactor (PWR) fuel In Canada deuterium uranium (CANDU) reactors (DUPIC) fuel fabrication plant was studied, which annually converts spent PWR fuel of 400 tonnes heavy element (HE) into CANDU fuel. The capital and operating costs were estimated from the viewpoint of conceptual design. Assuming that the annual discount rate is 5% during the construction (5 yr) and operation period (40 yr) and contingency is 25% of the capital cost, the levelized unit cost (LUC) of DUPIC fuel fabrication was estimated to be 616 $/kg HE, which is mostly governed by annual operation and maintenance costs that correspond to 63% of LUC. Among the operation and maintenance cost components being considered, the waste disposal cost has the dominant effect on LUC (~49%). From sensitivity analyses of production capacity, discount rate, and contingency, it was found that the production capacity of the plant is the major parameter that affects the LUC.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.019
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.199
Teacher spread0.188 · 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

Citations18
Published2001
Admission routes1
Has abstractyes

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