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Record W2606095421 · doi:10.1016/j.net.2017.04.002

On the effect of temperature on the threshold stress intensity factor of delayed hydride cracking in light water reactor fuel cladding

2017· article· en· W2606095421 on OpenAlexaboutno aff
Anna-Maria Alvarez Holston, Johan Stjärnsäter

Bibliographic record

VenueNuclear Engineering and Technology · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsCladding (metalworking)CrackingBurnupBoiling water reactorHydrideHydrogenMaterials scienceBoilingLight-water reactorMetallurgyComposite materialNuclear engineeringChemistryNuclear chemistry

Abstract

fetched live from OpenAlex

Delayed hydride cracking (DHC) was first observed in pressure tubes in Canadian CANDU reactors. In light water reactors, DHC was not observed until the late 1990s in high-burnup boiling water reactor (BWR) fuel cladding. In recent years, the focus on DHC has resurfaced in light of the increased interest in the cladding integrity during interim conditions. In principle, all spent fuel in the wet pools has sufficient hydrogen content for DHC to operate below 300°C. It is therefore of importance to establish the critical parameters for DHC to operate. This work studies the threshold stress intensity factor (KIH) to initiate DHC as a function of temperature in Zry-4 for temperatures between 227°C and 315°C. The experimental technique used in this study was the pin-loading testing technique. To determine the KIH, an unloading method was used where the load was successively reduced in a stepwise manner until no cracking was observed during 24 hours. The results showed that there was moderate temperature behavior at lower temperatures. Around 300°C, there was a sharp increase in KIH indicating the upper temperature limit for DHC. The value for KIH at 227°C was determined to be 2.6 ± 0.3 MPa √m.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.008
GPT teacher head0.195
Teacher spread0.187 · 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 designBench or experimental
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

Citations15
Published2017
Admission routes1
Has abstractyes

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