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Record W4414943015 · doi:10.1115/pvp2025-151777

Modelling of Local Hydrogen Isotope Concentration at Rolled Joints of CANDU Reactor Fuel Channels and Evaluation of Potential Interaction With an Adjacent Flaw

2025· article· en· W4414943015 on OpenAlexaff
Sreehari Ramachandra Prabhu, Dennis Kawa, Doug Scarth, Monique Ip, Shawn Lowe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsOntario Power GenerationBruce Power (Canada)Kinectrics (Canada)
Fundersnot available
KeywordsInletTube (container)HydrogenPressure vesselDiffusionInternal pressureCorrosionFinite element method

Abstract

fetched live from OpenAlex

Abstract The pressure tubes in CANDU-PHWR (Pressurized Heavy Water Reactor) are subject to various ageing related degradation mechanisms, including ingress of deuterium, which is a hydrogen isotope, through a corrosion reaction with the heavy water coolant. Pressure tube structural integrity is dependent on the hydrogen equivalent concentration, Heq, which accounts for both hydrogen and deuterium, and increases with reactor operating time. In recent Heq measurements, high Heq levels were observed at local areas of some pressure tubes that were in service for long operating times. This local area of high Heq is referred to as a “blip”. This paper investigates the modelling of blip formation at the inlet rolled region and its interaction with an incident postulated blunt flaw residing on the pressure tube inside surface at the blip axial location using a comprehensive three-dimensional finite element diffusion model of the fuel channel and a set of generic inputs. The analysis results indicate that the presence of a blip has a minimal effect on the build-up of hydrides at a postulated blunt flaw-tip of a flaw residing at the pressure tube inside surface at the blip axial location over long operating times.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.261
Teacher spread0.222 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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