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Record W2290699411 · doi:10.14288/1.0081015

The feasibility of using supercritical carbon dioxide as a coolant for the CANDU reactor

2010· article· en· W2290699411 on OpenAlexaffabout
Samsun Kwok-Sun Tom

Bibliographic record

VenuecIRcle (University of British Columbia) · 2010
Typearticle
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCoolantSupercritical fluidSupercritical carbon dioxideCarbon dioxideNuclear engineeringEnvironmental scienceMaterials scienceProcess engineeringChemistryEngineeringThermodynamicsMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

This study indicates the technical feasibility of using supercritical carbon dioxide as a coolant for a CANDU-type reactor. A new concept of supercritical cooling loop is proposed in this study. The reactor is cooled by a single phase coolant, which is pumped at a high density liquid-like state. The supercritical-fluid-cooled reactor has the advantage of avoiding dryout as in gas-cooled reactors, and the advantage of low coolant-circulation power as for liquid-cooled reactors. As a result of eliminating dryout, the maximum operating temperature of the fuel sheath can be increased to 1021°F (550°C) for existing Canadian fuel bundles. Accordingly, the coolant temperature in the case study of this work was calculated to be 855°F. This high temperature coolant can produce steam at a temperature and pressure comparable to that of conventional fossil-fuel plants. However, since the exit coolant temperature from the steam generator may be as low as 280°F, a portion of the supercritical carbon dioxide coolant is used to produce low-pressure steam. A new dual-reheat cycle is proposed to reduce the high degree of irreversibility in the steam generation process. In the new dual-reheat cycle, the coolant heats the low and high pressure feeds in a parallel manner instead of alternative heating as in dual-pressure cycles. The ideal overall plant efficiency of the new proposed dual-reheat cycle is 33.02%, which is comparable to that of the Pickering generating station.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.188
Teacher spread0.176 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2010
Admission routes2
Has abstractyes

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