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Record W2766076063 · doi:10.1115/pvp2017-66201

Fitness-for-Service Assessment of Steam Generator Tubing Subject to Dealloying Degradation

2017· article· en· W2766076063 on OpenAlexafffundabout
Rosita Mousavi, Xinjian Duan, Michael J. Kozluk, Min Wang, Yihai Shi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHigh Temperature Alloys and Creep
Canadian institutionsOntario Power Generation
FundersCanadian Nuclear Safety Commission
KeywordsBoiler (water heating)Service lifeMonelEngineeringGenerator (circuit theory)Service (business)Scope (computer science)Mechanical engineeringForensic engineeringProcess engineeringNuclear engineeringReliability engineeringWaste managementMaterials scienceMetallurgyComputer scienceAlloyPower (physics)

Abstract

fetched live from OpenAlex

A new degradation mechanism has been observed in Monel 400 Steam Generator tubing material, a nickel-copper alloy (63Ni-28Cu-2½Fe) with the ASME material designation SB-163/N04400. The location is above the top preheater support plate of the two re-circulating steam generator in one of the units of the Pickering Nuclear Generating Station. This paper provides a brief description of the regulatory environment, OPG’s steam generator life cycle management plans, the Canadian Industry’s fitness-for-service guidelines for steam generator tubes, and the afflicted steam generators. The paper then goes on to discuss the following activities that were conducted to support the technical basis to justify that the steam generators fit to be returned to service: • Inspection scope expansion, methods, and results. • Examination of removed tubes. • Condition monitoring assessment. • Operational assessment. • Burst-pressure tests of removed tubes and of fabricated test specimens. • Degradation specific flaw model and acceptance standards. • Flaw growth rate predictions. • Plugging limit adopted.

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)0.000
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 score0.396
Threshold uncertainty score0.455

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.021
GPT teacher head0.286
Teacher spread0.265 · 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

Citations10
Published2017
Admission routes3
Has abstractyes

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