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Record W4230509138 · doi:10.1115/1.3147743

Overload Fracture of Hydrided Region at Simulated Blunt Flaws in Zr-2.5Nb Pressure Tube Material

2009· article· en· W4230509138 on OpenAlexafffundabout
Jun Cui, Gordon K. Shek, Zhirui Wang

Bibliographic record

VenueJournal of Pressure Vessel Technology · 2009
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsUniversity of TorontoKinectrics (Canada)
FundersCANDU Owners GroupUniversity of Manchester
KeywordsMaterials scienceHydrogenHydrideFracture (geology)MetallurgyStress (linguistics)DeuteriumComposite materialChemistryNuclear physics

Abstract

fetched live from OpenAlex

A crack initiation and growth mechanism known as delayed hydride cracking (DHC) is a concern for Zr-2.5Nb alloy pressure tubes of CANada Deuterium Uranium or CANDU (CANDU is a trademark of the Atomic Energy of Canada Limited, Ontario, Canada) nuclear reactors. DHC is a repetitive process that involves hydrogen diffusion, hydride precipitation, formation, and fracture of a hydrided region at a flaw tip. An overload occurs when the flaw-tip hydrided region is loaded to a stress, higher than that at which this region is formed. For the fitness-for-service assessment of the pressure tubes, it is required to demonstrate that the overload from the normal reactor operating and transient loading conditions will not fracture the hydrided region, and will not initiate DHC. In this work, several series of systematically designed, monotonically increasing load experiments are performed on specimens, prepared from an unirradiated pressure tube with hydrided region, formed at flaws with a root radius of 0.1 mm or 0.3 mm, under different hydride formation stresses and thermal histories. Crack initiation in the overload tests is detected by the acoustic emission technique. Test results indicate that the resistance to overload fracture is dependent on a variety of parameters including hydride formation stress, thermal history, hydrogen concentration, and flaw geometry.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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 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

Citations13
Published2009
Admission routes3
Has abstractyes

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