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Record W3015470758 · doi:10.1115/1.4046843

Analysis of Heat Transfer Characteristics of Canadian SCWR Fuel Assembly Concept

2020· article· en· W3015470758 on OpenAlexaffabout
Armando Nava Domínguez, Y.F. Rao, T. Beuthe

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2020
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsCanadian Nuclear Laboratories
Fundersnot available
KeywordsHeat transferCladding (metalworking)BundleNuclear engineeringSupercritical fluidTube (container)Mechanical engineeringMaterials scienceMechanicsThermodynamicsEngineeringPhysicsComposite material

Abstract

fetched live from OpenAlex

Abstract Canada is participating in the Generation IV (Gen IV) International Forum with a main focus on the pressure-tube-type supercritical water-cooled reactor (SCWR) concept. The subchannel code ASSERT-PV modified for SCWR applications was used to design the SCWR fuel assembly, specifically the fuel bundle. Several assumptions were required to model the fuel assembly, including the perfect insulation of (i) the central flow tube (i.e., no heat transfer through the central tube) and (ii) the pressure tube (i.e., no heat loss to the moderator). These two assumptions were considered as conservative, but they were not analyzed or assessed for their validity or accuracy. ASSERT-PV was upgraded to model the heat loss to the moderator, and an external CATHENA system code model was coupled to ASSERT-PV to model the heat transfer to the central flow tube. This paper describes these additional heat transfer components, and presents an assessment of these two assumptions for their impact on the prediction of maximum fuel cladding temperature.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.011
GPT teacher head0.207
Teacher spread0.196 · 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 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

Citations5
Published2020
Admission routes2
Has abstractyes

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