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Record W2767610627 · doi:10.1115/1.4038367

Irradiation Issues and Material Selection for Canadian SCWR Components

2017· article· en· W2767610627 on OpenAlexaffabout
Lori J. Walters, M.G. Wright, D. Guzonas

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsCanadian Nuclear Laboratories
Fundersnot available
KeywordsMaterials scienceNuclear engineeringNeutron fluxCreepCoolantLight-water reactorDuctility (Earth science)Stress corrosion crackingIrradiationCorrosionNeutronComposite materialNuclear physics

Abstract

fetched live from OpenAlex

The Canadian super critical water-cooled reactor (SCWR) concept requires materials to operate at higher temperatures than current generation III water-cooled reactors. Materials performance after radiation damage is an important design consideration. Materials that are both corrosion resistant and radiation damage tolerant are required. This paper summarizes the operating conditions including temperature, neutron flux, and residence time of in-core Canadian SCWR components. The focus is on the effects of irradiation on in-core components, including those exposed to a high neutron flux in the fuel assembly, the high pressure boundary between coolant and moderator, as well as the low-temperature, low-flux calandria vessel that contains the moderator. Although the extreme conditions and the broad range of SCWR in-core operating conditions present significant materials selection challenges, candidate alloys that can meet the performance requirements under most in-core conditions have been identified. However, for all candidate materials, insufficient data are available to unequivocally ensure acceptable performance and experimental irradiations of candidate core materials will be required. Research programs are to include out-of-pile tests on un-irradiated and irradiated alloys. Ideally, in-flux studies at appropriate temperatures, neutron spectrum, dose rate, duration, and coolant chemistry will be required. Characterization of the microstructure and the mechanical behavior including strength, ductility, swelling, fracture toughness, cracking, and creep on each of the in-core candidate materials will ensure their viability in the Canadian SCWR.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.246
Teacher spread0.229 · 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 designNot applicable
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

Citations3
Published2017
Admission routes2
Has abstractyes

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