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Record W4388191489 · doi:10.1115/1.4063889

Investigation of the Defect Width Effect on the Burst Capacity of Composite-Repaired Pipelines With Corrosion Defects Using Finite Element Analysis

2023· article· en· W4388191489 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Pressure Vessel Technology · 2023
Typearticle
Languageen
FieldEngineering
TopicStructural Integrity and Reliability Analysis
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComposite numberParametric statisticsFinite element methodMaterials scienceCorrosionStructural engineeringPipeline transportComposite materialEngineeringMechanical engineeringMathematics

Abstract

fetched live from OpenAlex

Abstract This study investigates the effect of the defect width on the burst capacity of corroded pipelines repaired with fiber reinforced polymer composite. Parametric finite element analyses are carried out to evaluate the burst capacities of composite-repaired pipes containing localized and full-circumferential corrosion defects. The analysis results indicate that burst capacities of composite-repaired pipes containing localized defects can be markedly lower than those of composite-repaired pipes with full-circumferential defects. The burst capacity model derived from the design equation recommended in the ASME PCC-2 code is found to be nonconservative for composite-repaired pipes with localized defects based on the parametric finite element analyses. An empirical equation for the defect width correction factor is then developed and shown to be highly effective in improving the predictive accuracy of the PCC-2 burst capacity model.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.478
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.225
Teacher spread0.208 · 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