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Record W4404369863 · doi:10.1115/pvp2024-123421

Load Carrying Capacities of Small-Diameter Pipe Bends Under Internal Pressure: Analytical and Computational Predicitions

2024· article· en· W4404369863 on OpenAlexaffabout
Nicholas Robinson, Xin Wang, Bogdan Wasiluk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicEngineering Structural Analysis Methods
Canadian institutionsCanadian Nuclear Safety CommissionCarleton University
Fundersnot available
KeywordsInternal pressureMaterials scienceMechanicsMechanical engineeringComputer scienceComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract The performance and embedded conservatism of common modeling approaches used for predicting load carrying capacities were evaluated for small-diameter pipe bends typically found in CANDU reactors. Comprehensive analyses were conducted using both an analytical approach and detailed finite element modelling with commercial code ABAQUS. Small diameter pipe bends, with and without local wall thinning, under loading by internal pressure were investigated. The adopted modelling approach incorporated variability in pipe bend geometry and the characterization of material properties. The results obtained indicate that load carrying capacities of small-diameter pipe bends, either with or without local wall thinning but characterized by uniform wall thickness and single parameter material strength are conservatively predicted with analytical models in principle based on the limit load approach. However, detailed finite element modelling is needed for obtaining more accurate predictions of plastic instability pressure for pipe bends with local wall thinning. The reported investigation provides technical insights into the modelling approaches presently used for predicting load carrying capacities of small-diameter pipe bends under internal pressure loading; in addition, it has explored embedded conservatism while recognizing the existence of involved uncertainties. The results obtained emphasize the importance of detailed characterization of pipe bend thickness and material strength in such engineering predictions. This work has been performed under Canadian Nuclear Safety Commission (CNSC) Research and Support (R&S) project R765.1. The insights obtained may be used to further assess embedded conservatism in fit for service evaluations of CANDU outlet feeders experiencing wall thinning due to Flow Accelerated Corrosion (FAC). In addition, supplementary information informs the activities related to lowering the minimum required thickness below 75% of a straight pipe thickness by Article NB-3640 of Section III of the ASME B&PV Code for design pressure.

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)0.002
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.018
GPT teacher head0.257
Teacher spread0.238 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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