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Record W1794302911 · doi:10.1520/stp12329s

Predicting Crack Instability Behaviour of Burst Tests from Small Specimens for Irradiated Zr-2.5Nb Pressure Tubes

2009· book-chapter· en· W1794302911 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueASTM International eBooks · 2009
Typebook-chapter
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsMaterials scienceIrradiationInstabilityComposite materialMechanicsNuclear physicsPhysics

Abstract

fetched live from OpenAlex

A scaling approach, based on the deformation J-integral at maximum load obtained from small specimens, is proposed for predicting the crack instability behaviour of burst tests on irradiated Zr-2.5Nb pressure tubes. An assessment of this approach is carried out by comparison with other toughness criteria such as the modified J-integral and the plastic work dissipation rate approach. The largest discrepancy between the different parameters occurs for materials of intermediate toughness which exhibit the most stable crack growth and tunnelling up to maximum load. A study of one material of intermediate toughness suggests crack-front tunnelling has a significant influence on the results obtained from the 17-mm-wide specimens. It is shown that for a tube of intermediate toughness the different approaches can significantly underpredict the extent of stable crack growth before instability in a burst test even after correcting for tunnelling. The usefulness of a scaling approach in reducing the discrepancy between the small- and large-scale specimen results for this material is demonstrated.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.555
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.033
GPT teacher head0.242
Teacher spread0.209 · 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