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Record W3194193758

Calandria Vessel Integrity Under Severe Accident Loads

2007· article· en· W3194193758 on OpenAlexfundno aff
D.L. Luxat, John Luxat

Bibliographic record

VenueNCSU Libraries Repository (North Carolina State University Libraries) · 2007
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity Network of Excellence in Nuclear Engineering
KeywordsAccident (philosophy)Forensic engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

This paper discusses the integrity of the calandria vessel of a CANDU reactor under severe accident loads.The potential failure modes of the vessel are identified.They include thermal creep failure, overpressure failure and mechanical overload failure.Thermal creep failure of the vessel can occur if film boiling occurs over a significant area at the bottom of calandria vessel, thereby causing the vessel wall to heat up.Overpressure failure can occur if large, sustained rapid steam generation associated with relocated core debris into the moderator fluid occurs and the generated steam cannot be adequately relieved through relief ducts.Overload failure would occur if the mass of relocated core debris is sufficient to produce stresses in the vessel wall that exceed ultimate tensile stress.The limits associated with these failure modes are evaluated and used to generate representative likelihoods of calandria vessel heat loads.. 1

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.146
Threshold uncertainty score0.291

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.212
Teacher spread0.203 · 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 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

Citations7
Published2007
Admission routes1
Has abstractno

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